[merkledb benchmark] implement simple write profile benchmark #3372
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x/merkledb/benchmarks/benchmark.go
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| func getMerkleDBConfig(promRegistry prometheus.Registerer) merkledb.Config { | ||
| const defaultHistoryLength = 300 |
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Let's use the same number as firewood of 120: https://github.com/ava-labs/firewood/blob/main/firewood/src/manager.rs#L21
| Hasher: merkledb.DefaultHasher, | ||
| RootGenConcurrency: 0, | ||
| HistoryLength: defaultHistoryLength, | ||
| ValueNodeCacheSize: units.MiB, |
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These seem really small. If I am reading this correctly, there is about 2Mb of total cache?
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I attempted to tweak this value, but it had no performance impact.
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| fmt.Printf("Initializing database.") | ||
| ticksCh := make(chan interface{}) |
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nit: do you really need this ticker? Might be easier to report every 100k rows or something.
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reporting every 100k rows doesn't work nicely because of the batch writing ( which blocks for a long time ).
x/merkledb/benchmarks/benchmark.go
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| const ( | ||
| defaultDatabaseEntries = 2000000 | ||
| databaseCreationBatchSize = 1000000 |
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Batch size is supposed to be 10k. This is 1M.
| return err | ||
| } | ||
| } | ||
| deleteDuration = time.Since(startDeleteTime) |
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You can avoid all this math and just report the raw number of deletes. Grafana can convert this to a rate for you.
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I've added both. I believe that my calculation would be more accurate, but let's have both for the time being.
| deleteRate = prometheus.NewGauge(prometheus.GaugeOpts{ | ||
| Namespace: "merkledb_bench", | ||
| Name: "entry_delete_rate", | ||
| Help: "The rate at which elements are deleted", | ||
| }) | ||
| updateRate = prometheus.NewGauge(prometheus.GaugeOpts{ | ||
| Namespace: "merkledb_bench", | ||
| Name: "entry_update_rate", | ||
| Help: "The rate at which elements are updated", | ||
| }) | ||
| insertRate = prometheus.NewGauge(prometheus.GaugeOpts{ | ||
| Namespace: "merkledb_bench", | ||
| Name: "entry_insert_rate", | ||
| Help: "The rate at which elements are inserted", | ||
| }) | ||
| batchWriteRate = prometheus.NewGauge(prometheus.GaugeOpts{ | ||
| Namespace: "merkledb_bench", | ||
| Name: "batch_write_rate", | ||
| Help: "The rate at which the batch was written", | ||
| }) |
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We should not be calculating the rates in the benchmark. The prometheus server should do this based on the counts.
| deleteRate = prometheus.NewGauge(prometheus.GaugeOpts{ | |
| Namespace: "merkledb_bench", | |
| Name: "entry_delete_rate", | |
| Help: "The rate at which elements are deleted", | |
| }) | |
| updateRate = prometheus.NewGauge(prometheus.GaugeOpts{ | |
| Namespace: "merkledb_bench", | |
| Name: "entry_update_rate", | |
| Help: "The rate at which elements are updated", | |
| }) | |
| insertRate = prometheus.NewGauge(prometheus.GaugeOpts{ | |
| Namespace: "merkledb_bench", | |
| Name: "entry_insert_rate", | |
| Help: "The rate at which elements are inserted", | |
| }) | |
| batchWriteRate = prometheus.NewGauge(prometheus.GaugeOpts{ | |
| Namespace: "merkledb_bench", | |
| Name: "batch_write_rate", | |
| Help: "The rate at which the batch was written", | |
| }) |
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I believe that it won't generate accurate results, since we're mixing batch writing and put in the same sequence.
I've included both the counter and the rate metrics so that we can get both numbers in the grafana.
x/merkledb/benchmarks/benchmark.go
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| err = mdb.Close() | ||
| if err != nil { | ||
| fmt.Fprintf(os.Stderr, "unable to close levelDB database : %v\n", err) | ||
| return err | ||
| } | ||
| err = levelDB.Close() | ||
| if err != nil { | ||
| fmt.Fprintf(os.Stderr, "unable to close merkleDB database : %v\n", err) | ||
| return err | ||
| } |
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The logs seem inverted here
| ValueNodeCacheSize: units.MiB, | ||
| IntermediateNodeCacheSize: 1024 * units.MiB, |
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How much memory are we using? Feels like we could probably increase these
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I've attempted to tweak these, but haven't seen any concrete gains. Adjusting the leveldb config was helpful, though.
x/merkledb/benchmarks/benchmark.go
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| startUpdateTime := time.Now() | ||
| for keyToUpdateIdx := low + ((*databaseEntries) / 2); keyToUpdateIdx < low+((*databaseEntries)/2)+databaseRunningUpdateSize; keyToUpdateIdx++ { | ||
| updateEntryKey := calculateIndexEncoding(keyToUpdateIdx) | ||
| updateEntryValue := calculateIndexEncoding(keyToUpdateIdx - ((*databaseEntries) / 2)) |
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This is incorrect, should be:
| updateEntryValue := calculateIndexEncoding(keyToUpdateIdx - ((*databaseEntries) / 2)) | |
| updateEntryValue := calculateIndexEncoding(low) |
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hmm.. I think that it's ok to use the low as you suggested, although using the above would yield different and unique values ( i.e. [low..low+5k] ).
| levelDB.Close() | ||
| }() | ||
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| low := uint64(0) |
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low never changes, and should be increased by 2.5k each pass
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good catch; fixed.
Why this should be merged
How this works
How this was tested